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Local Tour Guide Django

A Django-based web application for guiding users through local tour experiences. The app provides information about various local cultural, historical, and tourist sites based on user queries, integrating a chatbot that answers questions about local culture, history, hiking, religious sites, and more in their native language.

Features

  • User-Friendly Interface: Simple navigation to explore different locations and categories.
  • Tour Categories: Supports religious, cultural, hiking, history, and places to visit.
  • Multilingual Support: Answers user queries in their native language.
  • AI-Powered Chatbot: Engages users in real-time, providing context-based answers using advanced Natural Language Processing (NLP).
  • Search Functionality: Integrated semantic search pipeline for efficient retrieval of location data.
  • Knowledge Base Integration: Uses FAISS for storing and querying local tour information.

Project Structure

Local_Tour_Guide_Django/
├── manage.py
├── local_tour_guide/
│   ├── settings.py
│   ├── urls.py
│   ├── wsgi.py
├── chatbot/
│   ├── models.py
│   ├── views.py
│   ├── urls.py
├── templates/
│   ├── base.html
│   ├── index.html
│   ├── chatbot.html
└── static/
    ├── css/
    ├── js/

Requirements

  • Python: 3.7+
  • Django: 3.2+
  • FAISS: For fast similarity search in large datasets.
  • Hugging Face Transformers: For the chatbot's NLP functionality.

Install all dependencies with:

pip install -r requirements.txt

Setup Instructions

  1. Clone the Repository:

    git clone https://github.com/your-username/Local_Tour_Guide_Django.git
cd Local_Tour_Guide_Django

  2. Install Dependencies:

    pip install -r requirements.txt

  3. Set Up the Database:

    python manage.py migrate

  4. Run the Development Server:

    python manage.py runserver

  5. Access the Application: Open your web browser and go to http://127.0.0.1:8000/.

AI Chatbot Integration

The project integrates a custom chatbot to handle user queries regarding local tours. It is powered by a fine-tuned T5-base model for generating responses based on the context provided by the user.

Key technologies used:

  • Django Channels: For websocket and full duplex communication
  • FAISS: For indexing and retrieving relevant context from a local knowledge base.
  • T5-base Model: Fine-tuned for context-based generative answering.

Usage

  • Explore Categories: Browse through different categories such as religious, cultural, hiking, etc.
  • Ask Questions: Use the chatbot to ask questions about local culture, history, and tourist sites in your native language.
  • Search: Utilize the search bar to look for specific places to visit or information about historical events.